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AI-Driven Compliance for Safe Material Transport: Cover Loads AI

Ensure compliance in material transportation with Cover Loads, an AI-powered solution that monitors vehicles entering and exiting quarries. Detects and verifies the use of tarps for materials, enhancing safety and minimizing environmental risks.

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Industry-Type
Industry

Supply Chain & Manufacturing

Industry-Type
Devs on Team

1

App Type
App Type

Enterprise

Methodology Used
Methodology

Agile Scrum

Platform
Platform

.Net Application, Server

Client Country:
Tech Used

UK

Tech Used
Technologies Used:

Python,Pytorch,Tensorflow, Yolov4-tiny,Onnx, .Net, SQL

Client Intro

FP McCann is one of the UK's leading manufacturers in the construction industry, committed to high-quality solutions across various sectors such as buildings, drainage, and civil engineering. With a reputation for innovation and excellence, they have embraced our AI solution like "Cover Loads" to enhance compliance and safety in material transportation. This move signifies their dedication to leveraging cutting-edge technology for improving operational efficiency and adhering to environmental and safety standards in their projects.

Client Intro
Need for Innovation

Need for Innovation

In the construction and transportation sectors, ensuring materials are safely and correctly transported is crucial. Yet, the existing manual methods for monitoring these standards are slow and often inaccurate, leading to potential safety risks and environmental issues. Recognizing this gap, there's a clear need for a more effective, innovative solution that automates and enhances the accuracy of compliance checks, making the process more efficient and reliable for companies like FP McCann

Detailed Explanation of How it Works


morning

Step

01

Early Morning at the Quarry Entrance

A truck, filled to the brim with crucial building material, approaches the quarry's exit.

Capturing

Step

02

Capturing the Moment

Strategically positioned cameras click into action, capturing high-resolution images of the truck. These cameras are part of an intricate network, designed to feed live data into the "Cover Loads" system.

Technology

Step

03

The Heart of Technology

As the image data flows in, the YOLOv7 AI technology takes the stage. It's a deep learning model, recognized for its precision in object detection tasks. YOLOv7 quickly gets to work, identifying the truck in the image and scanning for the presence of a tarp covering the load.

Verification

Step

04

Compliance Verification

The AI doesn't stop at detection. It delves deeper, comparing the identified material against a comprehensive database of materials that mandates coverage during transport. This step is crucial for ensuring that specific materials are transported according to safety and environmental standards.

Assessment

Step

05

Assessment and Action

Upon detecting a tarp, the system evaluates its coverage quality. If the material is flagged as needing a tarp but is found uncovered or inadequately covered, "Cover Loads" shifts gears into its compliance assessment phase. It's here that the system determines the compliance status of the truck, based on the stringent guidelines it's programmed to uphold.

Reports

Step

06

Alerts and Reports

In instances where non-compliance is detected, the system doesn't just note it down; it springs into action. Automated alerts are generated, promptly notifying quarry managers and compliance officers. This immediate feedback loop allows for swift intervention, ensuring that the truck does not leave the quarry without meeting all safety and compliance requirements.

Ripple Effect

Step

07

The Ripple Effect

By automating this compliance process, "Cover Loads" not only streamlines operations at the quarry but also plays a pivotal role in enhancing road safety, preventing environmental harm, and ensuring that the construction industry's stringent standards are met without compromise.

Challenges, Solutions, and Achievements


Challenges Client Faced -

Manual Monitoring

Keeping track of whether vehicles properly use tarps for certain materials was largely manual, slow, and prone to errors.

Compliance Uncertainty

It was tough to be sure that all materials were covered according to safety and environmental standards.

Risk of Penalties

Failure to comply with regulations could lead to fines and damage the company's reputation.

Safety & Environmental Concerns

Improperly secured materials pose risks to safety and the environment, including potential accidents and pollution.

What we did to fix it -

Introduced AI Detection

Implemented the "Cover Loads" AI system for automatic vehicle and tarp detection, ensuring materials are correctly covered.

Automated Compliance Verification

Set up the system to automatically check if the transported material requires a tarp, based on a list of materials and rules.

Real-Time Monitoring and Alerts

Enabled the system to monitor vehicles in real-time and send alerts for any compliance issues, helping to address problems immediately.

Data-Driven Insights

The system provides reports and insights on compliance, helping to improve safety and efficiency in material transportation processes.

What we Achieved



Enhanced Inventory Management
Enhanced Inventory Management

Improved Compliance: Cover Loads significantly enhanced material transportation compliance through automated monitoring and enforcement processes.

Operational Efficiency
Operational Efficiency

Reduced Safety Risks: Real-time alerts minimized safety risks by promptly identifying non-compliance, lowering the potential for accidents and injuries.

Improved Responsiveness
Improved Responsiveness

Streamlined Operations: Cover Loads optimized quarry operations by automating compliance checks, saving time and resources previously spent on manual inspections.

Technological Advancement
Technological Advancement

Environmental Protection: Cover Loads promoted environmental stewardship by ensuring proper transportation practices, reducing the risk of environmental hazards

AI Features Implemented


Microcontroller and Sensor Modules
AI-Powered Object Detection

Our system uses advanced AI to identify vehicles and check if they're following tarp regulations.

Distance Measuring Module
Material Compliance Verification

Automatically verifies if the material being transported requires a tarp, according to safety standards.

I2C Communication
Real-time Compliance Assessment

Assesses vehicles in real-time to ensure they meet tarp usage rules, enhancing safety and compliance.

Distributed System Architecture
Automated Alerts for Violations

Sends instant alerts when a vehicle doesn't comply with the tarp regulations, allowing for immediate action.

BEFORE

before

AFTER

after
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